bonding_w_geimini
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Bonding W Geimini
Overview :
bonding_w_geimini is an image processing application developed on the Streamlit framework, allowing users to upload images for object detection via the Gemini API and draw bounding boxes directly on the images. This application leverages machine learning models to identify and locate objects within images, playing a significant role in fields like image analysis, data annotation, and automated image processing.
Target Users :
The target audience includes data scientists, image processing engineers, machine learning researchers, and individuals interested in automated image analysis. This product is particularly suited for users who need rapid and accurate image object detection and annotation, especially in scenarios requiring extensive image data labeling.
Total Visits: 474.6M
Top Region: US(19.34%)
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Use Cases
Automating the classification and annotation of product images for e-commerce websites
Assisting researchers in identifying specific cells or tissues in biomedical images
Real-time analysis of abnormal behaviors in video streams within security surveillance
Features
Supports uploading images in JPG, JPEG, and PNG formats
Detects objects via the Gemini API and returns bounding box coordinates
Visualizes detected bounding boxes on the images, allowing for custom labeling
Downloads images with bounding boxes included
Requires a Python 3.9 or higher runtime environment
Requires a valid Gemini API key
How to Use
Clone the repository locally: git clone https://github.com/AlexZhangji/bonding_w_geimini.git
Navigate to the project directory: cd bonding_w_geimini
Install the necessary Python packages
Run the Streamlit application: streamlit run bbox.py
Enter your Gemini API key in the sidebar
Click 'Browse Files' to upload local JPG, JPEG, or PNG images
Input a descriptive text prompt for object detection
Click the 'Process' button to send the image and prompt to the Gemini API
Wait for the results, as the processed image will display the detected object bounding boxes
Click 'Download Image with Bounding Boxes' to save the processed image
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